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All the Apache Streaming Projects: An Exploratory Guide | @BigDataExpo #Apache #BigData #OpenSource

The speed at which data is generated, consumed, processed, and analyzed is increasing at an unbelievably rapid pace

The speed at which data is generated, consumed, processed, and analyzed is increasing at an unbelievably rapid pace. Social media, the Internet of Things, ad tech, and gaming verticals are struggling to deal with the disproportionate size of data sets. These industries demand data processing and analysis in near real-time. Traditional Big Data-styled frameworks such as Apache Hadoop are not well-suited for these use cases.

As a result, multiple open source projects have been started in the last few years to deal with the streaming data. All were designed to process a never-ending sequence of records originating from more than one source. From Kafka to Beam, there are over a dozen Apache projects in various stages of completion.

With a high overlap, the current Apache streaming projects address similar scenarios. Users often find it confusing to choose the right open source stack for implementing a real-time stream processing solution. This article attempts to help customers navigate the complex maze of Apache streaming projects by calling out the key differentiators for each. We will discuss the use cases and key scenarios addressed by Apache Kafka, Apache Storm, Apache Spark, Apache Samza, Apache Beam and related projects.

Apache Flume
Apache Flume
is one of the oldest Apache projects designed to collect, aggregate, and move large data sets such as web server logs to a centralized location. It belongs to the data collection and single-event processing family of stream processing solutions. Flume is based on an agent-driven architecture in which the events generated by clients are streamed directly to Apache Hive, HBase or other data stores.

Flume’s configuration includes a source, channel, and sink. The source can be anything from a Syslog to the Twitter stream to an Avro endpoint. The channel defines how the stream is delivered to the destination. The valid options include Memory, JDBC, Kafka, File among others. The sink determines the destination where the stream gets delivered. Flume supports many sinks such as HDFS, Hive, HBase, ElasticSearch, Kafka and others.

Apache Flume is ideal for scenarios where the client infrastructure supports installing agents. The most popular use case is to stream logs from multiple sources to a central, persistent data store for further processing analysis.

Sample Use Case: Streaming logs from multiple sources capable of running JVM.

Read the article at The New Stack.

Janakiram MSV is an analyst, advisor, and architect. Follow him on Twitter,  Facebook and LinkedIn.

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More Stories By Janakiram MSV

Janakiram MSV heads the Cloud Infrastructure Services at Aditi Technologies. He was the founder and CTO of Get Cloud Ready Consulting, a niche Cloud Migration and Cloud Operations firm that recently got acquired by Aditi Technologies. In his current role, he leads a highly talented engineering team that focuses on migrating and managing applications deployed on Amazon Web Services and Microsoft Windows Azure Infrastructure Services.
Janakiram is an industry analyst with deep understanding of Cloud services. Through his speaking, writing and analysis, he helps businesses take advantage of the emerging technologies. He leverages his experience of engaging with the industry in developing informative and practical research, analysis and authoritative content to inform, influence and guide decision makers. He analyzes market trends, new products / features, announcements, industry happenings and the impact of executive transitions.
Janakiram is one of the first few Microsoft Certified Professionals on Windows Azure in India. Demystifying The Cloud, an eBook authored by Janakiram is downloaded more than 100,000 times within the first few months. He is the Chief Editor of a popular portal on Cloud called www.CloudStory.in that covers the latest trends in Cloud Computing. Janakiram is an analyst with the GigaOM Pro analyst network where he analyzes the Cloud Services landscape. He is a guest faculty at the International Institute of Information Technology, Hyderabad (IIIT-H) where he teaches Big Data and Cloud Computing to students enrolled for the Masters course. As a passionate speaker, he has chaired the Cloud Computing track at premier events in India.
He has been the keynote speaker at many premier conferences, and his seminars are attended by thousands of architects, developers and IT professionals. His sessions are rated among the best in every conference he participates.
Janakiram has worked at the world-class product companies including Microsoft Corporation, Amazon Web Services and Alcatel-Lucent. Joining as the first employee of Amazon Web Services in India, he was the AWS Technology Evangelist. Prior to that, Janakiram spent 10 years at Microsoft Corporation where he was involved in selling, marketing and evangelizing the Microsoft Application Platform and Tools.